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Sel. Top. Signal. Process."},{"key":"10.1016\/j.rcim.2024.102792_bib0045","article-title":"Visual-tactile fusion for transparent object grasping in complex backgrounds","author":"Li","year":"2023","journal-title":"IEEE Trans. Robot."},{"key":"10.1016\/j.rcim.2024.102792_bib0046","doi-asserted-by":"crossref","first-page":"1753","DOI":"10.2991\/ijcis.d.210531.001","article-title":"Tactile-visual fusion based robotic grasp detection method with a reproducible sensor","volume":"14","author":"Song","year":"2021","journal-title":"Int. J. Comput. Intell. 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Manuf."},{"key":"10.1016\/j.rcim.2024.102792_bib0057","article-title":"Feature sensing and robotic grasping of objects with uncertain information: a review","volume":"20","author":"Wang","year":"2020","journal-title":"Sensors"},{"key":"10.1016\/j.rcim.2024.102792_bib0053","doi-asserted-by":"crossref","DOI":"10.1017\/S0263574723001285","article-title":"A review of robotic grasp detection technology","author":"Dong","year":"2023","journal-title":"Robotica"},{"key":"10.1016\/j.rcim.2024.102792_bib0055","doi-asserted-by":"crossref","first-page":"1677","DOI":"10.1007\/s10462-020-09888-5","article-title":"Vision-based robotic grasping from object localization, object pose estimation to grasp estimation for parallel grippers: a review","volume":"54","author":"Du","year":"2021","journal-title":"Artif. Intell. 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Materiom."},{"key":"10.1016\/j.rcim.2024.102792_bib0063","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1080\/01691864.2019.1632222","article-title":"Atkeson, Recent progress in tactile sensing and sensors for robotic manipulation: can we turn tactile sensing into vision?","volume":"33","author":"Yamaguchi","year":"2019","journal-title":"Adv. Robot."},{"key":"10.1016\/j.rcim.2024.102792_bib0064","doi-asserted-by":"crossref","first-page":"14997","DOI":"10.1021\/acsami.9b02049","article-title":"Flexible, tunable, and ultrasensitive capacitive pressure sensor with microconformal graphene electrodes","volume":"11","author":"Yang","year":"2019","journal-title":"ACS Appl. Mater. 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Actuat. A"},{"key":"10.1016\/j.rcim.2024.102792_bib0075","article-title":"Grasp Control of a Cable-Driven Robotic Hand Using a PVDF Slip Detection Sensor","author":"Nikafrooz","year":"2022","journal-title":"ArXiv."},{"key":"10.1016\/j.rcim.2024.102792_bib0076","series-title":"IEEE International Conference on Robotics and Automation, Kobe, Japan","first-page":"2972","article-title":"IEEE, Tactile sensing for an anthropomorphic robotic hand: hardware and signal processing","author":"G\u00f6ger","year":"2009"},{"key":"10.1016\/j.rcim.2024.102792_bib0077","doi-asserted-by":"crossref","first-page":"1663","DOI":"10.1109\/JMEMS.2015.2470132","article-title":"The piezoresistive effect of SiC for MEMS sensors at high temperatures: a review","volume":"24","author":"Phan","year":"2015","journal-title":"J. Microelectromech. Syst."},{"key":"10.1016\/j.rcim.2024.102792_bib0078","doi-asserted-by":"crossref","DOI":"10.3390\/polym14193930","article-title":"Soft conductive hydrogel-based electronic skin for robot finger grasping manipulation","volume":"14","author":"Cheng","year":"2022","journal-title":"Polymers"},{"key":"10.1016\/j.rcim.2024.102792_bib0079","article-title":"Grasping force control of multi-fingered robotic hands through tactile sensing for object stabilization","volume":"20","author":"Deng","year":"2020","journal-title":"Sensors"},{"key":"10.1016\/j.rcim.2024.102792_bib0080","doi-asserted-by":"crossref","DOI":"10.3390\/machines9060119","article-title":"Robot grasping system and grasp stability prediction based on flexible tactile sensor array","volume":"9","author":"Li","year":"2021","journal-title":"Machines"},{"key":"10.1016\/j.rcim.2024.102792_bib0081","doi-asserted-by":"crossref","DOI":"10.1016\/j.sna.2022.113609","article-title":"Soft and flexible large-strain piezoresistive sensors: on implementing proprioception, object classification and curvature estimation systems in adaptive, human-like robot hands","volume":"341","author":"Yong","year":"2022","journal-title":"Sens. Actuat. A"},{"key":"10.1016\/j.rcim.2024.102792_bib0082","doi-asserted-by":"crossref","first-page":"336","DOI":"10.1089\/soro.2022.0014","article-title":"Flexible electronic skin for monitoring of grasping state during robotic manipulation","volume":"10","author":"Bao","year":"2023","journal-title":"Soft. Robot."},{"key":"10.1016\/j.rcim.2024.102792_bib0083","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.robot.2012.07.021","article-title":"Design of a flexible tactile sensor for classification of rigid and deformable objects","volume":"62","author":"Drimus","year":"2014","journal-title":"Rob. Auton. Syst."},{"key":"10.1016\/j.rcim.2024.102792_bib0084","doi-asserted-by":"crossref","first-page":"4147","DOI":"10.1109\/LRA.2019.2931248","article-title":"Dynamic identification of the franka emika panda robot with retrieval of feasible parameters using penalty-based optimization","volume":"4","author":"Gaz","year":"2019","journal-title":"IEEE Robot. Autom. Lett."},{"key":"10.1016\/j.rcim.2024.102792_bib0085","unstructured":"Robotiq, 3-finger adaptive robot gripper, http:\/\/robotiq.com\/en\/products\/industrial-robot-hand, (Accessed 12 May 2014)."},{"key":"10.1016\/j.rcim.2024.102792_bib0086","series-title":"2011 IEEE World Haptics Conference","first-page":"615","article-title":"Sensing method of total-internal-reflection-based tactile sensor","author":"Koike","year":"2011"},{"key":"10.1016\/j.rcim.2024.102792_bib0087","unstructured":"SynTouch, The biotac, http:\/\/www.syntouchllc.com\/Products\/BioTac\/, (Accessed 12 May 2014)."},{"key":"10.1016\/j.rcim.2024.102792_bib0088","series-title":"2012 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)","first-page":"138","article-title":"Tactile image based contact shape recognition using neural network","author":"Liu","year":"2012"},{"key":"10.1016\/j.rcim.2024.102792_bib0089","unstructured":"Schunk, 2-finger-parallel gripper, http:\/\/www.schunk.com\/schunk_files\/attachments\/OM_AU_PG__EN.pdf, (Accessed 29 April 2014)."},{"key":"10.1016\/j.rcim.2024.102792_bib0090","series-title":"25th IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain","first-page":"2963","article-title":"Tactile Regrasp: Grasp adjustments via simulated tactile transformations","author":"Hogan","year":"2018"},{"key":"10.1016\/j.rcim.2024.102792_bib0091","series-title":"25th International Conference on Artificial Neural Networks (ICANN), Barcelona, SPAIN","first-page":"12","article-title":"Tactile convolutional networks for online slip and rotation detection","author":"Meier","year":"2016"},{"key":"10.1016\/j.rcim.2024.102792_bib0092","series-title":"IEEE-Computer-Society Conference on Computer Vision and Pattern Recognition Workshops, Miami Beach, FL","first-page":"1070","article-title":"Ieee, Retrographic sensing for the measurement of surface texture and shape","author":"Johnson","year":"2009"},{"key":"10.1016\/j.rcim.2024.102792_bib0093","series-title":"16th IEEE-RAS International Conference on Humanoid Robots (Humanoids), Mexican Assoc Comp Vis Robot & Neural Comp, Cancun, Mexico","first-page":"1045","article-title":"Atkeson, Combining finger vision and optical tactile sensing: reducing and handling errors while cutting vegetables","author":"Yamaguchi","year":"2016"},{"key":"10.1016\/j.rcim.2024.102792_bib0094","series-title":"Conference on Robot Learning, PMLR","first-page":"1395","article-title":"Towards learning to detect and predict contact events on vision-based tactile sensors","author":"Zhang","year":"2020"},{"key":"10.1016\/j.rcim.2024.102792_bib0095","doi-asserted-by":"crossref","first-page":"4094","DOI":"10.1109\/LRA.2019.2930477","article-title":"Effective estimation of contact force and torque for vision-based tactile sensors with helmholtz-hodge decomposition","volume":"4","author":"Zhang","year":"2019","journal-title":"IEEE Robot. Autom. Lett."},{"key":"10.1016\/j.rcim.2024.102792_bib0096","series-title":"IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia","first-page":"7772","article-title":"IEEE, Slip detection with combined tactile and visual information","author":"Li","year":"2018"},{"key":"10.1016\/j.rcim.2024.102792_bib0097","doi-asserted-by":"crossref","DOI":"10.3390\/s17122762","article-title":"GelSight: high-resolution robot tactile sensors for estimating geometry and force","volume":"17","author":"Yuan","year":"2017","journal-title":"Sensors"},{"key":"10.1016\/j.rcim.2024.102792_bib0098","doi-asserted-by":"crossref","first-page":"3838","DOI":"10.1109\/LRA.2020.2977257","article-title":"DIGIT: a novel design for a low-cost compact high-resolution tactile sensor with application to in-hand manipulation","volume":"5","author":"Lambeta","year":"2020","journal-title":"IEEE Robot. Autom. Lett."},{"key":"10.1016\/j.rcim.2024.102792_bib0099","unstructured":"\"GelSight, GelSight-Mini,\" https:\/\/www.gelsight.com\/gelsightmini.html."},{"key":"10.1016\/j.rcim.2024.102792_bib0100","series-title":"25th IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain","first-page":"1927","article-title":"GelSlim: a high-resolution, compact, robust, and calibrated tactile-sensing finger","author":"Donlon","year":"2018"},{"key":"10.1016\/j.rcim.2024.102792_bib0101","series-title":"IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Electr Network","first-page":"9903","article-title":"IEEE, GelTip: a finger-shaped optical tactile sensor for robotic manipulation","author":"Gomes","year":"2020"},{"key":"10.1016\/j.rcim.2024.102792_bib0102","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1089\/soro.2017.0052","article-title":"The TacTip family: soft optical tactile sensors with 3D-printed biomimetic morphologies","volume":"5","author":"Ward-Cherrier","year":"2018","journal-title":"Soft. Robot."},{"key":"10.1016\/j.rcim.2024.102792_bib0103","series-title":"IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids), Birmingham, England","first-page":"241","article-title":"Atkeson, IEEE, implementing tactile behaviors using fingervision","author":"Yamaguchi","year":"2017"},{"key":"10.1016\/j.rcim.2024.102792_bib0104","doi-asserted-by":"crossref","first-page":"512","DOI":"10.1109\/TOH.2014.2326159","article-title":"Incrementally learning objects by touch: online discriminative and generative models for tactile-based recognition","volume":"7","author":"Soh","year":"2014","journal-title":"IEEE Trans. Haptics."},{"key":"10.1016\/j.rcim.2024.102792_bib0105","doi-asserted-by":"crossref","first-page":"522","DOI":"10.1109\/TNNLS.2014.2316291","article-title":"Spatio-temporal learning with the online finite and infinite echo-state Gaussian processes","volume":"26","author":"Soh","year":"2015","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.rcim.2024.102792_bib0106","doi-asserted-by":"crossref","DOI":"10.1007\/s11432-017-9319-0","article-title":"Experiment on impedance adaptation of under-actuated gripper using tactile array under unknown environment","volume":"61","author":"Cui","year":"2018","journal-title":"Sci. China-Inf. Sci."},{"key":"10.1016\/j.rcim.2024.102792_bib0107","doi-asserted-by":"crossref","first-page":"656","DOI":"10.1109\/TIM.2016.2514779","article-title":"Object recognition using tactile measurements: kernel sparse coding methods","volume":"65","author":"Liu","year":"2016","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"10.1016\/j.rcim.2024.102792_bib0108","doi-asserted-by":"crossref","first-page":"4127","DOI":"10.1007\/s00170-017-0046-2","article-title":"Adaptive tactile control for in-hand manipulation tasks of deformable objects","volume":"91","author":"Delgado","year":"2017","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"10.1016\/j.rcim.2024.102792_bib0109","doi-asserted-by":"crossref","first-page":"4252","DOI":"10.1109\/LRA.2022.3151261","article-title":"Comparing single touch to dynamic exploratory procedures for robotic tactile object recognition","volume":"7","author":"Kirby","year":"2022","journal-title":"IEEE Robot. Autom. Lett."},{"key":"10.1016\/j.rcim.2024.102792_bib0110","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1016\/j.robot.2014.09.021","article-title":"Robotic learning of haptic adjectives through physical interaction","volume":"63","author":"Chu","year":"2015","journal-title":"Rob. Auton. Syst."},{"key":"10.1016\/j.rcim.2024.102792_bib0111","series-title":"IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, Peoples R China","first-page":"2262","article-title":"IEEE, ST-HMP: unsupervised spatio-temporal feature learning for tactile data","author":"Madry","year":"2014"},{"key":"10.1016\/j.rcim.2024.102792_bib0112","doi-asserted-by":"crossref","DOI":"10.1109\/TMAG.2018.2845894","article-title":"Detection and identification of object based on a magnetostrictive tactile sensing system","volume":"54","author":"Zhang","year":"2018","journal-title":"IEEE Trans. Magn."},{"key":"10.1016\/j.rcim.2024.102792_bib0113","series-title":"25th IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain","first-page":"1943","article-title":"Single-Grasp, model-free object classification using a hyper-adaptive hand, Google Soli, and tactile sensors","author":"Flintoff","year":"2018"},{"key":"10.1016\/j.rcim.2024.102792_bib0114","doi-asserted-by":"crossref","first-page":"2220","DOI":"10.1109\/LRA.2019.2902434","article-title":"A sense of touch for the shadow modular grasper","volume":"4","author":"Pestell","year":"2019","journal-title":"IEEE Robot. Autom. Lett."},{"key":"10.1016\/j.rcim.2024.102792_bib0115","series-title":"14th IEEE-RAS International Conference on Humanoid Robots (Humanoids), Madrid, Spain","first-page":"1044","article-title":"Sugano, IEEE, Tactile object recognition using deep learning and dropout","author":"Schmitz","year":"2014"},{"key":"10.1016\/j.rcim.2024.102792_bib0116","first-page":"1929","article-title":"Dropout: a simple way to prevent neural networks from overfitting","volume":"15","author":"Srivastava","year":"2014","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.rcim.2024.102792_bib0117","doi-asserted-by":"crossref","DOI":"10.3390\/s18030692","article-title":"Enhancing perception with tactile object recognition in adaptive grippers for human-robot interaction","volume":"18","author":"Gandarias","year":"2018","journal-title":"Sensors"},{"key":"10.1016\/j.rcim.2024.102792_bib0118","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1109\/TII.2019.2898264","article-title":"A deep learning framework for tactile recognition of known as well as novel objects","volume":"16","author":"Abderrahmane","year":"2020","journal-title":"IEEE Trans. Industr. Inform."},{"key":"10.1016\/j.rcim.2024.102792_bib0119","doi-asserted-by":"crossref","first-page":"486","DOI":"10.1108\/SR-08-2017-0160","article-title":"Multi-modal haptic image recognition based on deep learning","volume":"38","author":"Han","year":"2018","journal-title":"Sensor Rev."},{"key":"10.1016\/j.rcim.2024.102792_bib0120","series-title":"IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Electr Network","first-page":"9876","article-title":"Ieee, TactileSGNet: a spiking graph neural network for event-based tactile object recognition","author":"Gu","year":"2020"},{"key":"10.1016\/j.rcim.2024.102792_bib0121","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1109\/LRA.2020.3038377","article-title":"Bayesian and neural inference on LSTM-based object recognition from tactile and kinesthetic information","volume":"6","author":"Pastor","year":"2021","journal-title":"IEEE Robot. Autom. Lett."},{"key":"10.1016\/j.rcim.2024.102792_bib0122","series-title":"IEEE International Conference on Robotics and Biomimetics (IEEE ROBIO), Sanya, Peoples R China","first-page":"1570","article-title":"IEEE, Robotic tactile recognition system based on AM-LSTM model","author":"Xu","year":"2021"},{"key":"10.1016\/j.rcim.2024.102792_bib0123","doi-asserted-by":"crossref","DOI":"10.3390\/s19245356","article-title":"Using 3D convolutional neural networks for tactile object recognition with robotic palpation","volume":"19","author":"Pastor","year":"2019","journal-title":"Sensors"},{"key":"10.1016\/j.rcim.2024.102792_bib0124","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1016\/j.precisioneng.2021.12.009","article-title":"Identification of unknown object properties based on tactile motion sequence using 2-finger gripper robot","volume":"74","author":"Thompson","year":"2022","journal-title":"Precis. Eng."},{"key":"10.1016\/j.rcim.2024.102792_bib0132","doi-asserted-by":"crossref","first-page":"969","DOI":"10.1109\/TSMC.2016.2524059","article-title":"Object classification and grasp planning using visual and tactile sensing","volume":"46","author":"Sun","year":"2016","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."},{"key":"10.1016\/j.rcim.2024.102792_bib0133","doi-asserted-by":"crossref","first-page":"760","DOI":"10.1162\/neco.2006.18.4.760","article-title":"Modeling sensorimotor learning with linear dynamical systems","volume":"18","author":"Cheng","year":"2006","journal-title":"Neural Comput."},{"key":"10.1016\/j.rcim.2024.102792_bib0134","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/j.cviu.2014.04.011","article-title":"SHOT: unique signatures of histograms for surface and texture description","volume":"125","author":"Salti","year":"2014","journal-title":"Comput. Vis. 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Lett."},{"key":"10.1016\/j.rcim.2024.102792_bib0139","doi-asserted-by":"crossref","first-page":"987","DOI":"10.1109\/TRO.2019.2914772","article-title":"Learning approach to cross-modal object recognition: from visual observation to robotic haptic exploration","volume":"35","author":"Falco","year":"2019","journal-title":"IEEE Trans. Robot."},{"key":"10.1016\/j.rcim.2024.102792_bib0125","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1109\/LRA.2017.2734965","article-title":"Covering a robot fingertip with uSkin: a soft electronic skin with distributed 3-axis force sensitive elements for robot hands","volume":"3","author":"Tomo","year":"2018","journal-title":"IEEE Robot. Autom. Lett."},{"key":"10.1016\/j.rcim.2024.102792_bib0126","doi-asserted-by":"crossref","first-page":"1257","DOI":"10.1016\/j.measurement.2012.11.015","article-title":"Tactile sensors for robotic applications","volume":"46","author":"Girao","year":"2013","journal-title":"Measurement"},{"key":"10.1016\/j.rcim.2024.102792_bib0127","series-title":"IEEE International Conference on Robotics and Automation, Kobe, Japan","first-page":"3294","article-title":"IEEE, Design of human symbiotic robot twenty-one","author":"Iwata","year":"2009"},{"key":"10.1016\/j.rcim.2024.102792_bib0128","series-title":"International Conference on Inventive Computation Technologies (ICICT), Coimbatore, India","first-page":"279","article-title":"IEEE, Speech control pick and place robotic arm with flexiforce sensor","author":"Ramgire","year":"2016"},{"key":"10.1016\/j.rcim.2024.102792_bib0140","series-title":"2022 International Conference on Robotics and Automation (ICRA)","first-page":"6151","article-title":"Tata: a universal jamming gripper with high-quality tactile perception and its application to underwater manipulation","author":"Li","year":"2022"},{"key":"10.1016\/j.rcim.2024.102792_bib0141","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1109\/LRA.2015.2505061","article-title":"A conformable force\/tactile skin for physical human\u2013robot interaction","volume":"1","author":"Cirillo","year":"2015","journal-title":"IEEE Robot. Autom. Lett."},{"issue":"11","key":"10.1016\/j.rcim.2024.102792_bib0142","first-page":"2043","article-title":"3D pose tracking with multi-template warping and SIFT correspondences","volume":"26","author":"Chen","year":"2016","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.rcim.2024.102792_bib0143","article-title":"R, KochPose estimation from line correspondences: a complete analysis and a series of solutions","author":"Xu","year":"2016","journal-title":"IEEE Trans. Pattern Anal. Mach. 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Robot."},{"key":"10.1016\/j.rcim.2024.102792_bib0147","doi-asserted-by":"crossref","DOI":"10.3390\/s22176470","article-title":"Model-based 3D contact geometry perception for visual tactile sensor","volume":"22","author":"Ji","year":"2022","journal-title":"Sensors"},{"key":"10.1016\/j.rcim.2024.102792_bib0148","doi-asserted-by":"crossref","first-page":"4686","DOI":"10.1109\/LRA.2022.3150045","article-title":"Active visuo-tactile interactive robotic perception for accurate object pose estimation in dense clutter","volume":"7","author":"Murali","year":"2022","journal-title":"IEEE Robot. Autom. Lett."},{"key":"10.1016\/j.rcim.2024.102792_bib0149","series-title":"IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Kyoto, Japan","first-page":"3233","article-title":"IEEE, Simultaneous contact location and object pose estimation using proprioception and tactile feedback","author":"Sipos","year":"2022"},{"key":"10.1016\/j.rcim.2024.102792_bib0150","doi-asserted-by":"crossref","first-page":"1139","DOI":"10.1109\/TRO.2017.2707092","article-title":"Memory unscented particle filter for 6-DOF tactile localization","volume":"33","author":"Vezzani","year":"2017","journal-title":"IEEE Trans. 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Robot."},{"key":"10.1016\/j.rcim.2024.102792_bib0154","series-title":"IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Tokyo, Japan","first-page":"4013","article-title":"Sequential trajectory re-planning with tactile information gain for dexterous grasping under object-pose uncertainty","author":"Zito","year":"2013"},{"key":"10.1016\/j.rcim.2024.102792_bib0155","series-title":"20th International Conference on Advanced Robotics (ICAR), Electr Network","first-page":"948","article-title":"IEEE, Simultaneous tactile localization and reconstruction of an object during robotic manipulation","author":"Kissoum","year":"2021"},{"key":"10.1016\/j.rcim.2024.102792_bib0156","series-title":"Conference on Robot Learning, PMLR","first-page":"1596","article-title":"Visuotactile affordances for cloth manipulation with local control","author":"Sunil","year":"2023"},{"key":"10.1016\/j.rcim.2024.102792_bib0157","article-title":"Tactile object pose estimation from the first touch with geometric contact rendering","author":"Bauza","year":"2020","journal-title":"ArXiv."},{"key":"10.1016\/j.rcim.2024.102792_bib0158","series-title":"IEEE International Conference on Robotics and Automation (ICRA), Xian, Peoples R China","first-page":"1622","article-title":"IEEE, Towards integrated tactile sensorimotor control in anthropomorphic soft robotic hands","author":"Lepora","year":"2021"},{"key":"10.1016\/j.rcim.2024.102792_bib0159","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1109\/MRA.2020.2979658","article-title":"Optimal deep learning for robot touch: training accurate pose models of 3D surfaces and edges","volume":"27","author":"Lepora","year":"2020","journal-title":"IEEE Robot. 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Lett."},{"key":"10.1016\/j.rcim.2024.102792_bib0163","series-title":"IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Chicago, IL","first-page":"2733","article-title":"IEEE, Real-time object pose recognition and tracking with an imprecisely calibrated moving RGB-D camera","author":"Pauwels","year":"2014"},{"key":"10.1016\/j.rcim.2024.102792_bib0164","series-title":"4th Iberian Robotics Conference (Robot) - Advances in Robotics, Porto, Portugal","first-page":"184","article-title":"Visual and tactile fusion for estimating the pose of a grasped object","author":"Alvarez","year":"2019"},{"key":"10.1016\/j.rcim.2024.102792_bib0165","series-title":"IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Tokyo, japan","first-page":"4021","article-title":"Combining touch and vision for the estimation of an object's pose during manipulation","author":"Bimbo","year":"2013"},{"key":"10.1016\/j.rcim.2024.102792_bib0166","doi-asserted-by":"crossref","first-page":"2148","DOI":"10.1109\/LRA.2022.3143289","article-title":"VisuoTactile 6D Pose estimation of an in-hand object using vision and tactile sensor data","volume":"7","author":"Dikhale","year":"2022","journal-title":"IEEE Robot. 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Lett."},{"key":"10.1016\/j.rcim.2024.102792_bib0167","series-title":"IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Electr Network","first-page":"6786","article-title":"IEEE, visual-tactile fusion for 3D objects reconstruction from a single depth view and a single gripper touch for robotics Tasks","author":"Tahoun","year":"2021"},{"key":"10.1016\/j.rcim.2024.102792_bib0168","doi-asserted-by":"crossref","first-page":"17218","DOI":"10.1109\/ACCESS.2023.3244552","article-title":"In-hand pose estimation using hand-mounted RGB cameras and visuotactile sensors","volume":"11","author":"Gao","year":"2023","journal-title":"IEEE Access"},{"key":"10.1016\/j.rcim.2024.102792_bib0169","series-title":"IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids), Toronto, Canada","first-page":"402","article-title":"IEEE, Visuo-haptic grasping of unknown objects based on gaussian process implicit surfaces and deep learning","author":"Ottenhaus","year":"2019"},{"key":"10.1016\/j.rcim.2024.102792_bib0170","series-title":"IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Electr Network","first-page":"9361","article-title":"IEEE, Deep Gated multi-modal learning: in-hand object pose changes estimation using tactile and image data","author":"Anzai","year":"2020"},{"key":"10.1016\/j.rcim.2024.102792_bib0171","series-title":"IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada","first-page":"7339","article-title":"IEEE, Multi-modal geometric learning for grasping and manipulation","author":"Watkins-Valls","year":"2019"},{"key":"10.1016\/j.rcim.2024.102792_bib0173","doi-asserted-by":"crossref","first-page":"969","DOI":"10.1109\/TASE.2021.3054655","article-title":"Weight imprinting classification-based force grasping with a variable-stiffness robotic gripper","volume":"19","author":"Zhu","year":"2022","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"10.1016\/j.rcim.2024.102792_bib0174","doi-asserted-by":"crossref","DOI":"10.1002\/admt.202100285","article-title":"Finger-skin-inspired flexible optical sensor for force sensing and slip detection in robotic grasping","volume":"6","author":"Jiang","year":"2021","journal-title":"Adv. Mater. 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Mechatron."},{"key":"10.1016\/j.rcim.2024.102792_bib0178","doi-asserted-by":"crossref","first-page":"1117","DOI":"10.1109\/TRO.2007.910774","article-title":"Fast computation of optimal contact forces","volume":"23","author":"Boyd","year":"2007","journal-title":"IEEE Trans. Robot."},{"key":"10.1016\/j.rcim.2024.102792_bib0179","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1007\/s10107-010-0419-x","article-title":"Statistical ranking and combinatorial Hodge theory","volume":"127","author":"Jiang","year":"2011","journal-title":"Math. Program."},{"key":"10.1016\/j.rcim.2024.102792_bib0180","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1016\/j.robot.2017.04.017","article-title":"Tactile control based on Gaussian images and its application in bi-manual manipulation of deformable objects","volume":"94","author":"Delgado","year":"2017","journal-title":"Rob. Auton. Syst."},{"key":"10.1016\/j.rcim.2024.102792_bib0181","series-title":"4th IEEE International Conference on Cyborg and Bionic Systems (CBS), Wuhan, Peoples R China","first-page":"49","article-title":"IEEE, Visual Tactile sensor based force estimation for position-force teleoperation","author":"Zhu","year":"2023"},{"key":"10.1016\/j.rcim.2024.102792_bib0182","doi-asserted-by":"crossref","first-page":"11767","DOI":"10.1109\/LRA.2022.3205768","article-title":"A Soft barometric tactile sensor to simultaneously localize contact and estimate normal force with validation to detect slip in a robotic gripper","volume":"7","author":"De Clercq","year":"2022","journal-title":"IEEE Robot. Autom. Lett."},{"key":"10.1016\/j.rcim.2024.102792_bib0183","series-title":"IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia","first-page":"4740","article-title":"IEEE, A dual-model vision-based tactile sensor for robotic hand grasping","author":"Fang","year":"2018"},{"key":"10.1016\/j.rcim.2024.102792_bib0184","doi-asserted-by":"crossref","first-page":"173438","DOI":"10.1109\/ACCESS.2019.2956882","article-title":"Ground truth force distribution for learning-based tactile sensing: a finite element approach","volume":"7","author":"Sferrazza","year":"2019","journal-title":"IEEE Access."},{"key":"10.1016\/j.rcim.2024.102792_bib0185","article-title":"Artificial intelligence-based optimal grasping control","volume":"20","author":"Kim","year":"2020","journal-title":"Sensors"},{"key":"10.1016\/j.rcim.2024.102792_bib0186","doi-asserted-by":"crossref","first-page":"676","DOI":"10.1109\/TFUZZ.2006.883415","article-title":"A survey on analysis and design of model-based fuzzy control systems","volume":"14","author":"Feng","year":"2006","journal-title":"IEEE Trans. Fuzzy Syst."},{"key":"10.1016\/j.rcim.2024.102792_bib0187","series-title":"IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada","first-page":"9035","article-title":"IEEE, Robust learning of tactile force estimation through robot interaction","author":"Sundaralingam","year":"2019"},{"key":"10.1016\/j.rcim.2024.102792_bib0188","series-title":"IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Kyoto, Japan","first-page":"3651","article-title":"IEEE, Learning-based six-axis force\/torque estimation using GelStereo fingertip visuotactile sensing","author":"Zhang","year":"2022"},{"key":"10.1016\/j.rcim.2024.102792_bib0199","year":"2014"},{"key":"10.1016\/j.rcim.2024.102792_bib0189","series-title":"International Conference on Control, Automation and Systems (ICCAS 2010), Gyeonggi do, South Korea","first-page":"1456","article-title":"IEEE, Analysis grasp stability for multi-fingered robot hand","author":"Kim","year":"2010"},{"key":"10.1016\/j.rcim.2024.102792_bib0190","series-title":"2013 IEEE International Conference on Robotics and Automation","first-page":"3040","article-title":"A probabilistic framework for task-oriented grasp stability assessment","author":"Bekiroglu","year":"2013"},{"issue":"4","key":"10.1016\/j.rcim.2024.102792_bib0191","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1177\/0278364912471690","article-title":"On the mechanics of natural compliance in frictional contacts and its effect on grasp stiffness and stability","volume":"32","author":"Shapiro","year":"2013","journal-title":"Int. J. Robot. Res."},{"key":"10.1016\/j.rcim.2024.102792_bib0192","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1007\/s10514-013-9355-y","article-title":"Stable grasping under pose uncertainty using tactile feedback","volume":"36","author":"Dang","year":"2014","journal-title":"Auton Robots"},{"key":"10.1016\/j.rcim.2024.102792_bib0193","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1007\/s11263-013-0620-5","article-title":"Selective search for object recognition","volume":"104","author":"Uijlings","year":"2013","journal-title":"Int. J. Comput. Vis."},{"key":"10.1016\/j.rcim.2024.102792_bib0194","series-title":"IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA","first-page":"4927","article-title":"IEEE, Learning the tactile signatures of prototypical object parts for robust part-based grasping of novel objects","author":"Hyttinen","year":"2015"},{"key":"10.1016\/j.rcim.2024.102792_bib0195","doi-asserted-by":"crossref","first-page":"6822","DOI":"10.1109\/LRA.2022.3151260","article-title":"A robotic grasping state perception framework with multi-phase tactile information and ensemble learning","volume":"7","author":"Yan","year":"2022","journal-title":"IEEE Robot. Autom. Lett."},{"key":"10.1016\/j.rcim.2024.102792_bib0196","series-title":"IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, Canada","first-page":"286","article-title":"Grasp stability assessment through the fusion of proprioception and tactile signals using convolutional neural networks","author":"Kwiatkowski","year":"2017"},{"key":"10.1016\/j.rcim.2024.102792_bib0197","series-title":"19th IEEE International Conference on Mechatronics and Automation (IEEE ICMA), Electr Network","first-page":"651","article-title":"IEEE, Robot grasping stability prediction network based on feature-fusion and feature-reconstruction of tactile information","author":"Li","year":"2022"},{"key":"10.1016\/j.rcim.2024.102792_bib0198","series-title":"Integration of Resources in Industrial Robotics: A Service-Oriented Approach","author":"Cardoso","year":"2011"},{"key":"10.1016\/j.rcim.2024.102792_bib0200","doi-asserted-by":"crossref","DOI":"10.3390\/app13020921","article-title":"Detecting and controlling slip through estimation and control of the sliding velocity","volume":"13","author":"Costanzo","year":"2023","journal-title":"Appl. Sci."},{"key":"10.1016\/j.rcim.2024.102792_bib0201","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1016\/S0947-3580(98)70113-X","article-title":"Friction models and friction compensation","volume":"4","author":"Olsson","year":"1998","journal-title":"Eur. J. Control"},{"key":"10.1016\/j.rcim.2024.102792_bib0202","doi-asserted-by":"crossref","DOI":"10.1016\/j.measurement.2022.111906","article-title":"Incipient slip detection method for soft objects with vision-based tactile sensor","volume":"203","author":"Sui","year":"2022","journal-title":"Measurement"},{"key":"10.1016\/j.rcim.2024.102792_bib0203","doi-asserted-by":"crossref","first-page":"1477","DOI":"10.1016\/S0022-5096(03)00053-X","article-title":"Experiments and theory in strain gradient elasticity","volume":"51","author":"Lam","year":"2003","journal-title":"J. Mech. Phys. Solids."},{"key":"10.1016\/j.rcim.2024.102792_bib0204","doi-asserted-by":"crossref","first-page":"1115","DOI":"10.1109\/TRO.2020.3043675","article-title":"In-hand object-dynamics inference using tactile fingertips","volume":"37","author":"Sundaralingam","year":"2021","journal-title":"IEEE Trans. Robot."},{"key":"10.1016\/j.rcim.2024.102792_bib0205","series-title":"IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada","first-page":"3818","article-title":"IEEE, Maintaining grasps within slipping bounds by monitoring incipient slip","author":"Dong","year":"2019"},{"key":"10.1016\/j.rcim.2024.102792_bib0206","doi-asserted-by":"crossref","first-page":"153364","DOI":"10.1109\/ACCESS.2020.3017738","article-title":"Neuromorphic event-based slip detection and suppression in robotic grasping and manipulation","volume":"8","author":"Muthusamy","year":"2020","journal-title":"IEEE Access."},{"key":"10.1016\/j.rcim.2024.102792_bib0207","doi-asserted-by":"crossref","first-page":"1047","DOI":"10.3233\/JAE-2012-1577","article-title":"Slip detection with multi-axis force\/torque sensor in universal robot hand","volume":"39","author":"Kobayashi","year":"2012","journal-title":"Int. J. Appl. Electromag. Mech."},{"key":"10.1016\/j.rcim.2024.102792_bib0208","first-page":"365","article-title":"Multilayer-perceptron-based slip detection algorithm using normal force sensor arrays","volume":"35","author":"Bamshad","year":"2023","journal-title":"Sens. Mater."},{"key":"10.1016\/j.rcim.2024.102792_bib0209","doi-asserted-by":"crossref","first-page":"506","DOI":"10.1109\/TRO.2020.3031245","article-title":"Slip detection for grasp stabilization with a multifingered tactile robot hand","volume":"37","author":"James","year":"2021","journal-title":"IEEE Trans. Robot."},{"key":"10.1016\/j.rcim.2024.102792_bib0210","article-title":"Learning-based slip detection for robotic fruit grasping and manipulation under leaf interference","volume":"22","author":"Zhou","year":"2022","journal-title":"Sensors"},{"key":"10.1016\/j.rcim.2024.102792_bib0211","series-title":"15th IEEE-RAS International Conference on Humanoid Robots (Humanoids), Seoul, South Korea","first-page":"297","article-title":"IEEE, Force estimation and slip detection\/classification for grip control using a biomimetic tactile sensor","author":"Su","year":"2015"},{"key":"10.1016\/j.rcim.2024.102792_bib0212","doi-asserted-by":"crossref","first-page":"5827","DOI":"10.1109\/LRA.2020.3010720","article-title":"Self-attention based visual-tactile fusion learning for predicting grasp outcomes","volume":"5","author":"Cui","year":"2020","journal-title":"IEEE Robot. Autom. Lett."},{"key":"10.1016\/j.rcim.2024.102792_bib0213","unstructured":"Y. Han, R. Batra, N. Boyd, T. Zhao, Y. She, S. Hutchinson, Y. Zhao, Learning generalizable vision-tactile robotic grasping strategy for deformable objects via transformer, arXiv preprint arXiv:2112.06374, (2021)."},{"key":"10.1016\/j.rcim.2024.102792_bib0214","series-title":"31st Annual Conference on Neural Information Processing Systems (NIPS), Long Beach, CA","article-title":"Attention is all you need","author":"Vaswani","year":"2017"},{"key":"10.1016\/j.rcim.2024.102792_bib0215","series-title":"IEEE International Conference on Robotics and Automation (ICRA), Electr Network","first-page":"538","article-title":"IEEE, Grasp state assessment of deformable objects using visual-tactile fusion perception","author":"Cui","year":"2020"},{"key":"10.1016\/j.rcim.2024.102792_bib0216","doi-asserted-by":"crossref","first-page":"26863","DOI":"10.1109\/JSEN.2023.3319114","article-title":"PTFD-Net: a sliding detection algorithm combining point cloud sequences and tactile sequences information","volume":"23","author":"Li","year":"2023","journal-title":"IEEE Sens. J."},{"key":"10.1016\/j.rcim.2024.102792_bib0217","series-title":"16th Conference on Robotics - Science and Systems (RSS), Electr Network","article-title":"Event-driven visual-tactile sensing and learning for robots","author":"Taunyazov","year":"2020"},{"key":"10.1016\/j.rcim.2024.102792_bib0218","doi-asserted-by":"crossref","first-page":"6370","DOI":"10.1109\/LRA.2021.3092770","article-title":"Softness-adaptive pinch-grasp strategy using fingertip tactile information of robot hand","volume":"6","author":"Park","year":"2021","journal-title":"IEEE Robot. Autom. Lett."},{"key":"10.1016\/j.rcim.2024.102792_bib0219","doi-asserted-by":"crossref","first-page":"1067","DOI":"10.1109\/TRO.2011.2162271","article-title":"Human-inspired robotic grasp control with tactile sensing","volume":"27","author":"Romano","year":"2011","journal-title":"IEEE Trans. Robot."},{"key":"10.1016\/j.rcim.2024.102792_bib0220","first-page":"3","article-title":"Properties of cutaneous mechanoreceptors in the human hand related to touch sensation","volume":"3","author":"Vallbo","year":"1984","journal-title":"Hum. Neurobiol."},{"key":"10.1016\/j.rcim.2024.102792_bib0221","series-title":"IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Chicago, IL","first-page":"3339","article-title":"IEEE, Learning of grasp adaptation through experience and tactile sensing","author":"Li","year":"2014"},{"key":"10.1016\/j.rcim.2024.102792_bib0222","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1207\/S15328007SEM1101_10","article-title":"The elements of statistical learning: data mining, inference and prediction","volume":"11","author":"Marcoulides","year":"2004","journal-title":"Struct. Eq. Model.-A"},{"key":"10.1016\/j.rcim.2024.102792_bib0223","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1162\/neco.1989.1.3.295","article-title":"Unsupervised learning","volume":"1","author":"Barlow","year":"1989","journal-title":"Neural Comput."},{"key":"10.1016\/j.rcim.2024.102792_bib0224","article-title":"Reinforcement learning: a survey","author":"Kaelbling","year":"1996","journal-title":"ArXiv."},{"key":"10.1016\/j.rcim.2024.102792_bib0225","series-title":"IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, South Korea","first-page":"1960","article-title":"IEEE, Self-supervised regrasping using spatio-temporal tactile features and reinforcement learning","author":"Chebotar","year":"2016"},{"key":"10.1016\/j.rcim.2024.102792_bib0226","series-title":"International Symposium on Experimental Robotics (ISER), Buenos Aires, Argentina","first-page":"375","article-title":"Learning to grasp without seeing","author":"Murali","year":"2018"},{"key":"10.1016\/j.rcim.2024.102792_bib0227","article-title":"MAT: multi-Fingered Adaptive Tactile Grasping via Deep Reinforcement Learning","author":"Wu","year":"2019","journal-title":"ArXiv."},{"key":"10.1016\/j.rcim.2024.102792_bib0228","series-title":"15th International Symposium on Experimental Robotics (ISER), Tokyo, Japan","first-page":"622","article-title":"Generalizing regrasping with supervised policy learning","author":"Chebotar","year":"2016"},{"key":"10.1016\/j.rcim.2024.102792_bib0229","article-title":"Bayesian Grasp: robotic visual stable grasp based on prior tactile knowledge","author":"Xue","year":"2019","journal-title":"ArXiv."},{"key":"10.1016\/j.rcim.2024.102792_bib0230","doi-asserted-by":"crossref","first-page":"3300","DOI":"10.1109\/LRA.2018.2852779","article-title":"More than a feeling: learning to grasp and regrasp using vision and touch","volume":"3","author":"Calandra","year":"2018","journal-title":"IEEE Robot. Autom. Lett."},{"key":"10.1016\/j.rcim.2024.102792_bib0231","series-title":"IEEE International Conference on Robotics and Automation (ICRA), Electr Network","first-page":"610","article-title":"IEEE, center-of-mass-based robust grasp planning for unknown objects using tactile-visual sensors","author":"Feng","year":"2020"},{"key":"10.1016\/j.rcim.2024.102792_bib0232","doi-asserted-by":"crossref","first-page":"960","DOI":"10.1109\/TRO.2016.2588879","article-title":"Hierarchical fingertip space: a unified framework for grasp planning and in-hand grasp adaptation","volume":"32","author":"Hang","year":"2016","journal-title":"IEEE Trans. Robot."},{"key":"10.1016\/j.rcim.2024.102792_bib0233","series-title":"15th IEEE-RAS International Conference on Humanoid Robots (Humanoids), Seoul, South Korea","first-page":"704","article-title":"IEEE, Task-specific grasping of similar objects by probabilistic fusion of vision and tactile measurements","author":"Kolycheva","year":"2015"},{"key":"10.1016\/j.rcim.2024.102792_bib0234","series-title":"2015 International Conference on Advanced Robotics (ICAR","first-page":"510","article-title":"The YCB object and Model set: towards common benchmarks for manipulation research","author":"Calli","year":"2015"},{"key":"10.1016\/j.rcim.2024.102792_bib0235","series-title":"2011 IEEE International Conference on Robotics and Automation (ICRA)","first-page":"3304","article-title":"Efficient grasping from RGBD images: learning using a new rectangle representation","author":"Jiang S","year":"2011"},{"key":"10.1016\/j.rcim.2024.102792_bib0236","series-title":"IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)","first-page":"3511","article-title":"Jacquard: a large scale dataset for robotic grasp detection","author":"Depierre","year":"2018"},{"key":"10.1016\/j.rcim.2024.102792_bib0237","doi-asserted-by":"crossref","DOI":"10.3389\/frobt.2023.1038658","article-title":"Learning-based robotic grasping: a review","volume":"10","author":"Xie","year":"2023","journal-title":"Front. Robot. AI."},{"issue":"3","key":"10.1016\/j.rcim.2024.102792_bib0238","first-page":"4210","article-title":"A reconfigurable design for omni-adaptive grasp learning","volume":"5","author":"Wan","year":"2020","journal-title":"IEEE Robot. Autom. Lett."},{"key":"10.1016\/j.rcim.2024.102792_bib0239","doi-asserted-by":"crossref","DOI":"10.1002\/aisy.202200371","article-title":"Machine learning for tactile perception: advancements, challenges, and opportunities","author":"Hu","year":"2023","journal-title":"Adv. Intell. Syst."},{"key":"10.1016\/j.rcim.2024.102792_bib0240","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1186\/s40537-016-0043-6","article-title":"A survey of transfer learning","volume":"3","author":"Weiss","year":"2016","journal-title":"J. Big. 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